SoroushVahidi/scidocs huggingface dataset:
Analyzing Enterprise Architecture in National Governments: The Cases of Denmark and the Netherlands
(2007)

National enterprise architectures (NEA) promise to fill the gap between policy and implementation. NEAs are embedded within an institutional environment consisting of active players capable of responding strategically and innovatively to architectural initiatives, which might complicate NEA adoption. In this paper we analyze the efforts of two European national governments in developing enterprise architecture. Grounded in institutional theory and practice we develop an analytical framework and use this framework to analyze the efforts of two countries, Denmark and the Netherlands. Our framework and analysis draws the attention to the need to take a broader perspective on enterprise architecture, especially governance aspects determine the adoption and diffusion of NEA
A Cross Tenant Access Control (CTAC) Model for Cloud Computing: Formal Specification and Verification
(2017)

Sharing of resources on the cloud can be achieved on a large scale, since it is cost effective and location independent. Despite the hype surrounding cloud computing, organizations are still reluctant to deploy their businesses in the cloud computing environment due to concerns in secure resource sharing. In this paper, we propose a cloud resource mediation service offered by cloud service providers, which plays the role of trusted third party among its different tenants. This paper formally specifies the resource sharing mechanism between two different tenants in the presence of our proposed cloud resource mediation service. The correctness of permission activation and delegation mechanism among different tenants using four distinct algorithms (activation, delegation, forward revocation, and backward revocation) is also demonstrated using formal verification. The performance analysis suggests that the sharing of resources can be performed securely and efficiently across different tenants of the cloud.
Applying Deep Learning to Better Predict Cryptocurrency Trends
(2018)

In this paper, we will create deep learning models using the Python library, Keras, to make predictions on Bitcoin. We designed two neural networks to make similar predictions with important differences. In our first approach, we created a simple neural net with one input layer and an additional dropout layer to generate a continuous value. This continuous value is the predicted price of the Bitcoin a week from the given input. For the second model, we attempted to predict whether or not the price of the Bitcoin would go up 3%, stay within 3%, or go down 3% a week from a given date. Instead of returning a single continuous value, the result contains an array of three values. Each value is a percentage of the likelihood that it will either go up 3%, stay within 3%, or go down 3%. We approached designing the models using many different optimizers, activation functions, number of neurons, and various quantities of layers before settling on the final models. We also compared three different optimizers for each problem: Stochastic Gradient Descent (SGD), Adam, and RMSProp. We compared the results of all three optimizers to determine which one was the most effective at creating the most accurate model.
Using ontologies to improve semantic interoperability in health data.
(2015)

The present-day health data ecosystem comprises a wide array of complex heterogeneous data sources. A wide range of clinical, health care, social and other clinically relevant information are stored in these data sources. These data exist either as structured data or as free-text. These data are generally individual person-based records, but social care data are generally case based and less formal data sources may be shared by groups. The structured data may be organised in a proprietary way or be coded using one-of-many coding, classification or terminologies that have often evolved in isolation and designed to meet the needs of the context that they have been developed. This has resulted in a wide range of semantic interoperability issues that make the integration of data held on these different systems changing. We present semantic interoperability challenges and describe a classification of these. We propose a four-step process and a toolkit for those wishing to work more ontologically, progressing from the identification and specification of concepts to validating a final ontology. The four steps are: (1) the identification and specification of data sources; (2) the conceptualisation of semantic meaning; (3) defining to what extent routine data can be used as a measure of the process or outcome of care required in a particular study or audit and (4) the formalisation and validation of the final ontology. The toolkit is an extension of a previous schema created to formalise the development of ontologies related to chronic disease management. The extensions are focused on facilitating rapid building of ontologies for time-critical research studies.
Generating Responses Expressing Emotion in an Open-domain Dialogue System
(2018)

Neural network-based Open-ended conversational agents automatically generate responses based on predictive models learned from a large number of pairs of utterances. The generated responses are typically acceptable as a sentence but are often dull, generic, and certainly devoid of any emotion. In this paper we present neural models that learn to express a given emotion in the generated response. We propose four models and evaluate them against 3 baselines. An encoder-decoder framework-based model with multiple attention layers provides the best overall performance in terms of expressing the required emotion. While it does not outperform other models on all emotions, it presents promising results in most cases.
Horse Racing Prediction Using Artificial Neural Networks
(2010)

Artificial Neural Networks (ANNs) have been applied to predict many complex problems. In this paper ANNs are applied to horse racing prediction. We employed Back-Propagation, Back-Propagation with Momentum, QuasiNewton, Levenberg-Marquardt and Conjugate Gradient Descent learning algorithms for real horse racing data and the performances of five supervised NN algorithms were analyzed. Data collected from AQUEDUCT Race Track in NY, include 100 actual races from 1 January to 29 January 2010. The experimental results demonstrate that NNs are appropriate methods in horse racing prediction context. Results show that BP algorithm performs slightly better than other algorithms but it needs a longer training time and more parameter selection. Furthermore, LM algorithm is the fastest. Key-Words: Artificial Neural Networks, Time Series Analysis, Horse Racing Prediction, Learning Algorithms, BackPropagation
CellDesigner: a process diagram editor for gene-regulatory and biochemical networks
(2003)

Systems biology is characterized by synergistic integration of theory, computational modeling, and experiment. Though software infrastructure is one of the most critical components of systems biology research, there has been no common infrastructure or standard to enable integration of computational resources. To solve this problem, the Systems Biology Markup Language (SBML) [2] and Systems Biology Workbench (SBW) have been developed. A number of simulation and analysis software packages already support SBML and SBW, or are in the process to support it. An identification of logic and dynamics of gene-regulatory and biochemical networks is a major challenge of systems biology. We believe that such network building tools and simulation environments using standardized technologies play an important role in software platform of systems biology. As one of the approaches, we have developed CellDesigner [1], which is a process diagram editor for gene-regulatory and biochemical networks.
SVMs — a practical consequence of learning theory
(1998)

Bernhard Schölkopf, GMD First Is there anything worthwhile to learn about the new SVM algorithm, or does it fall into the category of “yet-another-algorithm,” in which case readers should stop here and save their time for something more useful? In this short overview, I will try to argue that studying support-vector learning is very useful in two respects. First, it is quite satisfying from a theoretical point of view: SV learning is based on some beautifully simple ideas and provides a clear intuition of what learning from examples is about. Second, it can lead to high performances in practical applications. In the following sense can the SV algorithm be considered as lying at the intersection of learning theory and practice: for certain simple types of algorithms, statistical learning theory can identify rather precisely the factors that need to be taken into account to learn successfully. Real-world applications, however, often mandate the use of more complex models and algorithms—such as neural networks—that are much harder to analyze theoretically. The SV algorithm achieves both. It constructs models that are complex enough: it contains a large class of neural nets, radial basis function (RBF) nets, and polynomial classifiers as special cases. Yet it is simple enough to be analyzed mathematically, because it can be shown to correspond to a linear method in a high-dimensional feature space nonlinearly related to input space. Moreover, even though we can think of it as a linear algorithm in a high-dimensional space, in practice, it does not involve any computations in that high-dimensional space. By the use of kernels, all necessary computations are performed directly in input space. This is the characteristic twist of SV methods—we are dealing with complex algorithms for nonlinear pattern recognition, 1 regression, 2 or feature extraction,3 but for the sake of analysis and algorithmics, we can pretend that we are working with a simple linear algorithm. I will explain the gist of SV methods by describing their roots in learning theory, the optimal hyperplane algorithm, the kernel trick, and SV function estimation. For details and further references, see Vladimir Vapnik’s authoritative treatment, 2 he collection my colleagues and I have put together, 4 and the SV Web page at http://svm. first.gmd.de.
Off-Line Arabic Character Recognition – A Review
(2002)

Off-line recognition requires transferring the text under consideration into an image file. This represents the only available solution to bring the printed materials to the electronic media. However, the transferring process causes the system to lose the temporal information of that text. Other complexities that an off-line recognition system has to deal with are the lower resolution of the document and the poor binarisation, which can contribute to readability when essential features of the characters are deleted or obscured. Recognising Arabic script presents two additional challenges: orthography is cursive and letter shape is context sensitive. Certain character combinations form new ligature shapes, which are often font-dependent. Some ligatures involve vertical stacking of characters. Since not all letters connect, word boundary location becomes an interesting problem, as spacing may separate not only words, but also certain characters within a word. Various techniques have been implemented to achieve high recognition rates. These techniques have tackled different aspects of the recognition system. This review is organised into five major sections, covering a general overview, Arabic writing characteristics, Arabic text recognition system, Arabic OCR software and conclusions.
Broadband design of substrate integrated waveguide to stripline interconnect
(2014)

A broadband design of substrate integrated waveguide (SIW) to stripline interconnects is presented for the first time. The transition shows a wideband performance and, contrary to microstrip and coplanar waveguide circuitry, interconnects two planar transmission-line media that are both capable of medium-level power handling capabilities. Over a bandwidth of 18 GHz to 28 GHz (43.4 percent), the single interconnect shows a worst-case return loss of 24 dB and maximum insertion losses of 0.44 dB. For a back-to-back connection, the return loss reduces to 19 dB and insertion loss increases to 0.87 dB. All dimensional parameters are specified, and the design is validated by two commercially available field-solver packages. Moreover, field plots are presented that highlight the step-by-step mode conversion from SIW to stripline.
Deep Learning Powered In-Session Contextual Ranking using Clickthrough Data
(2016)

http://en.wikipedia.org/wiki/The_Dangerous_Days_of_Daniel_X http://en.wikipedia.org/wiki/The_Dangerous_Days_of_Daniel_X http://www.amazon.com/The-Dangerous-Days-Daniel-X/dp/0316119709 http://fanon.wikia.com/wiki/The_Dangerous_Days_of_Daniel_X http://www.goodreads.com/book/show/2235597.The_Dangerous_Days_of_Daniel_X http://www.amazon.com/The-Dangerous-Days-Daniel-X/dp/0316119709 http://www.daniel-x.co.uk/books/dangerous-days/ http://danielx.wikia.com/wiki/The_Dangerous_Days_of_Daniel_X_(novel) http://www.freebooknotes.com/summaries-analysis/the-dangerous-days-of-daniel-x/ http://danielx.wikia.com/wiki/Daniel_X http://www.jamespatterson.com/books_danielX.php#.VCR0vOfUe1A http://www.goodreads.com/series/49946-daniel-x http://jamespatterson.com/books_daniel_x.php#.VCR01efUe1A http://en.wikipedia.org/wiki/Daniel_X:_Watch_the_Skies http://books.google.com/books/about/The_Dangerous_Days_of_Daniel_X.html? id=2UBONTvr_BEC http://www.jamespatterson.com/books_danielX.php
High Vgs MOSFET characteristics with thin gate oxide for PMIC application
(2011)

We present the characteristics of a newly developed MOSFET which has thin gate oxide but sustains high gate voltage. It consists of MIM capacitor coupled floating gate poly and source/drain junction formed by low voltage well. The characteristics of the MOSFET depend on the choice of capacitance coupling ratio which is determined by the ratio of MIM (Metal-Insulator-Metal) capacitance and gate oxide capacitance. This means that the proper choice of layout can control the device performances; threshold voltage, ID-VD, and ID-VG characteristics. Some of smart power management ICs requires of a low density non-volatile memory for the purpose of PMIC trimming. To meet this purpose, NVM embedding on PMIC solution should be cost effective. This newly proposed high gate voltage MOSFET with thin gate oxide can be an effective solution for the periphery circuits of single poly EEPROM operation.
Wideband waveguide slot array antennas with corporate-feed in 120GHz and 350GHz bands
(2013)

We design and fabricate double-layer slotted waveguide array antennas with wide bandwidths and high efficiencies for 120 GHz and 350 GHz bands. To achieve high gain and high efficiency in high frequency bands, the diffusion bonding technique of plate laminated waveguide is used as a fabrication method. The antennas with 16×16 slots show about 70% efficiency with 32 dBi gain and about 50% efficiency with 31 dBi gain in the 120 GHz and 350 GHz bands, respectively.
DoS & DDoS in Named Data Networking
(2013)

With the growing realization that current Internet protocols are reaching the limits of their senescence, several ongoing research efforts aim to design potential next-generation Internet architectures. Although they vary in maturity and scope, in order to avoid past pitfalls, these efforts seek to treat security and privacy as fundamental requirements. Resilience to Denialof-Service (DoS) attacks that plague today’s Internet is a major issue for any new architecture and deserves full attention. In this paper, we focus on DoS in Named Data Networking (NDN) – a specific candidate for next-generation Internet architecture designs. By naming data instead of its locations, NDN transforms data into a first-class entity and makes itself an attractive and viable approach to meet the needs for many current and emerging applications. It also incorporates some basic security features that mitigate classes of attacks that are commonly seen today. However, NDN’s resilience to DoS attacks has not been analyzed to-date. This paper represents a first step towards assessment and possible mitigation of DoS in NDN. After identifying and analyzing several new types of attacks, it investigates their variations, effects and counter-measures. This paper also sheds some light on the debate about relative virtues of self-certifying, as opposed to human-readable, names in the context of content-centric networking.
ClaimEval: Integrated and Flexible Framework for Claim Evaluation Using Credibility of Sources
(2016)

The World Wide Web (WWW) has become a rapidly growing platform consisting of numerous sources which provide supporting or contradictory information about claims (e.g., “Chicken meat is healthy”). In order to decide whether a claim is true or false, one needs to analyze content of different sources of information on the Web, measure credibility of information sources, and aggregate all these information. This is a tedious process and the Web search engines address only part of the overall problem, viz., producing only a list of relevant sources. In this paper, we present ClaimEval, a novel and integrated approach which given a set of claims to validate, extracts a set of pro and con arguments from the Web information sources, and jointly estimates credibility of sources and correctness of claims. ClaimEval uses Probabilistic Soft Logic (PSL), resulting in a flexible and principled framework which makes it easy to state and incorporate different forms of prior-knowledge. Through extensive experiments on realworld datasets, we demonstrate ClaimEval’s capability in determining validity of a set of claims, resulting in improved accuracy compared to state-of-the-art baselines.
The reflective practitioner: How professionals think in action
(1985)

What do you do to start reading the reflective practitioner how professionals think in action arena ? Searching the book that you love to read first or find an interesting book that will make you want to read? Everybody has difference with their reason of reading a book. Actuary, reading habit must be from earlier. Many people may be love to read, but not a book. It's not fault. Someone will be bored to open the thick book with small words to read. In more, this is the real condition. So do happen probably with this the reflective practitioner how professionals think in action arena .
Systems Development in Information Systems Research
(1990)

In this paper, the use of systems development as a methodology in information systems (is) research is described and defended. A framework to explain the nature of systems development as a research methodology in is research is proposed. Use of this methodology in the engineering field in general is compared with its use specifically in computer science and computer engineering. An integrated program for conducting IS research that incorporates theory building, systems development, experimentation, and observation is proposed. Progress in several application domains is reviewed to provide a basis upon which to argue that systems development is a valid research methodology. A systems development research process is presented from a methodological perspective. Software engineering, which is the basic method of applying the systems development research methodology, is then discussed. It is the authors' belief that systems development and other research methodologies are complementary and that an integrated multi-dimensional and multimethodological approach will generate fruitful is research results. The premise is that research contributions can result from systems development, experimentation, observation, and performance testing of the systems under development and that all of these research approaches are needed to investigate different aspects of the research question. An earlier version of Ihis paper was originally published in the Proceedings of ihe Twenty-Third Hawaii International Conference on System Sciences (IEEE Computer Society Press, 1990). Journal of Management Information Systems I Winter 1990-91, Vol. 7, No, 3, pp. 89-106. Copyright © M. E. Sharpe, Inc., 1991. 90 NUNAMAKER, CHEN. AND PURDIN
PUBLIC DEBT AND GROWTH
(2010)

This paper examines the impact of high public debt on long-run economic growth in a panel of advanced and emerging economies over four decades, while taking into account various estimation issues including reverse causality and endogeneity. Threshold effects, non-linearities, and differences between advanced and emerging market economies are also explored. High initial public debt is found to be significantly and consistently associated with slower subsequent growth, controlling for other determinants of growth. The adverse effect largely reflects a slowdown in labor productivity growth mainly due to reduced investment and slower growth of capital stock. Extensive robustness checks confirm the results.
Loihi: A Neuromorphic Manycore Processor with On-Chip Learning
(2018)

Loihi is a 60-mm2 chip fabricated in Intels 14-nm process that advances the state-of-the-art modeling of spiking neural networks in silicon. It integrates a wide range of novel features for the field, such as hierarchical connectivity, dendritic compartments, synaptic delays, and, most importantly, programmable synaptic learning rules. Running a spiking convolutional form of the Locally Competitive Algorithm, Loihi can solve LASSO optimization problems with over three orders of magnitude superior energy-delay-product compared to conventional solvers running on a CPU iso-process/voltage/area. This provides an unambiguous example of spike-based computation, outperforming all known conventional solutions.
Towards improved genome-scale metabolic network reconstructions: unification, transcript specificity and beyond
(2015)

Genome-scale metabolic network reconstructions provide a basis for the investigation of the metabolic properties of an organism. There are reconstructions available for multiple organisms, from prokaryotes to higher organisms and methods for the analysis of a reconstruction. One example is the use of flux balance analysis to improve the yields of a target chemical, which has been applied successfully. However, comparison of results between existing reconstructions and models presents a challenge because of the heterogeneity of the available reconstructions, for example, of standards for presenting gene-protein-reaction associations, nomenclature of metabolites and reactions or selection of protonation states. The lack of comparability for gene identifiers or model-specific reactions without annotated evidence often leads to the creation of a new model from scratch, as data cannot be properly matched otherwise. In this contribution, we propose to improve the predictive power of metabolic models by switching from gene-protein-reaction associations to transcript-isoform-reaction associations, thus taking advantage of the improvement of precision in gene expression measurements. To achieve this precision, we discuss available databases that can be used to retrieve this type of information and point at issues that can arise from their neglect. Further, we stress issues that arise from non-standardized building pipelines, like inconsistencies in protonation states. In addition, problems arising from the use of non-specific cofactors, e.g. artificial futile cycles, are discussed, and finally efforts of the metabolic modelling community to unify model reconstructions are highlighted.